Passage assisting method, device and equipment and storage medium
By acquiring scene perception information of traffic signs and lines for risk assessment and differentiated control, the safety hazards of the LCC system in zebra crossings without traffic lights have been resolved, improving traffic safety and user experience.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-26
- Publication Date
- 2026-04-03
AI Technical Summary
Existing LCC systems struggle to effectively determine whether pedestrians are obstructed by obstacles in complex intersection environments, especially at crosswalks without traffic lights and where visibility is limited, leading to safety hazards for vehicles.
By acquiring scene perception information of traffic signs and lines, including the operating status of adjacent vehicles and lane attribute information, risk level assessment is conducted, and differentiated traffic control strategies, including warning, braking and exit strategies, are implemented based on the assessment results.
It enables autonomous risk assessment and differentiated control in complex intersection environments, improving traffic safety and driving experience, and avoiding collision risks caused by pedestrians being obstructed by obstacles.
Smart Images
Figure CN121777972A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of vehicle control technology, and in particular to a traffic assistance method, device, equipment and storage medium. Background Technology
[0002] Lane Centering Control (LCC) is a widely used function in Advanced Driving Assistance Systems (ADAS) that helps vehicles perform follow-the-car cruise control and lane centering. While LCC has reached a relatively mature stage, real-world road scenarios are complex and varied. Therefore, LCC needs to be tailored to specific complex scenarios to ensure the safety of occupants and enhance the driving experience, making it more natural and human-centered.
[0003] The current problem is that when a LCC (Lane Crossing Control) approaches a crosswalk, it struggles to decide whether to slow down or continue through the intersection due to obstructions such as vehicles in adjacent lanes. Existing solutions involve predicting lateral movement of pedestrians within the driver's field of vision at the crosswalk and braking accordingly, or proceeding at a normal, steady speed if no pedestrian is detected. This approach is somewhat rigid. If a pedestrian is obstructed and undetected, continuing through can easily lead to a collision, especially in scenarios like internal roads in residential areas or small urban intersections lacking traffic lights. Currently, there is a lack of effective judgment mechanisms for crosswalk scenarios without traffic lights and with obstructed visibility, posing a safety hazard.
[0004] Therefore, how to proactively respond to complex intersection environments and improve traffic safety has become an urgent problem to be solved. Summary of the Invention
[0005] The main objective of this application is to provide a traffic assistance method, device, equipment, and storage medium, which aims to solve the technical problem of how to achieve proactive response to complex intersection environments and improve traffic safety.
[0006] To achieve the above objectives, this application proposes a passage assistance method, which includes: In response to detecting that the traffic sign line meets the preset traffic assistance conditions, the scene perception information corresponding to the traffic sign line is obtained. The scene perception information includes the operating status information of adjacent vehicles and lane attribute information. Based on the scene perception information, a risk level assessment is performed on the road scene corresponding to the traffic sign line to obtain the risk assessment result. The corresponding access control strategy will be implemented based on the risk assessment results.
[0007] In one embodiment, the step of assessing the risk level of the road scene corresponding to the traffic sign based on the scene perception information and obtaining the risk assessment result includes: When a preset braking state is detected in the neighboring vehicle operating status information, the number of braking neighboring vehicles corresponding to the vehicle in the braking state is obtained. The braking lane position corresponding to the vehicle in the braking state is obtained based on the lane attribute information. When the number of adjacent vehicles braking and the direction of the braking lane meet the preset high-risk conditions, the scenario is determined to be high-risk.
[0008] In one embodiment, the step of executing the corresponding access control strategy based on the risk assessment result includes: When the risk assessment result is a high-risk scenario, obtain the early warning information corresponding to the high-risk scenario; Determine the target braking deceleration based on the target braking distance and the current vehicle speed; Based on the warning information, the target braking deceleration, and the target braking distance, a preset braking strategy is executed until the preset passage assistance conditions are not met, at which point the preset braking strategy is exited.
[0009] In one embodiment, the step of assessing the risk level of the road scene corresponding to the traffic sign based on the scene perception information and obtaining the risk assessment result includes: When a turning state is detected in the neighboring vehicle's operating status information, the turning lane information and turning lane spacing corresponding to the vehicle in the turning state are obtained according to the lane attribute information. If the turning lane information matches the preset turning lane, the turning lane spacing is greater than the preset vehicle spacing, and the vehicle in the turning state brakes, it is determined to be a medium-risk scenario.
[0010] In one embodiment, after obtaining the turning lane information and turning lane spacing corresponding to the vehicle in the turning state based on the lane attribute information when a turning state is detected in the neighboring vehicle's operating state information, the method further includes: If the turning lane information matches the preset straight lane, the turning lane spacing is less than the preset vehicle spacing, and the vehicle in the turning state brakes, it is determined to be a low-risk scenario.
[0011] In one embodiment, the step of assessing the risk level of the road scene corresponding to the traffic sign based on the scene perception information and obtaining the risk assessment result includes: When a stopped state is detected in the neighboring vehicle's operating status information, the stopping lane information and stopping lane spacing corresponding to the vehicle in the stopped state are obtained according to the lane attribute information. If the stopping lane information matches the preset boundary lane and the stopping lane spacing is greater than the preset vehicle spacing, the scenario is determined to be low-risk.
[0012] In one embodiment, before obtaining scene perception information corresponding to the traffic sign line in response to detecting that the traffic sign line meets preset traffic assistance conditions, the method further includes: Obtain the actual perceived length of traffic sign lines; Obtain the traffic signal status corresponding to the traffic sign line; If the actual perceived length is less than the theoretical length of the traffic marking line, and the traffic signal status is that no traffic light is detected, then the traffic marking line is determined to meet the preset passage assistance conditions.
[0013] Furthermore, to achieve the above objectives, this application also proposes a passage assistance device, which includes: The auxiliary start module is used to obtain scene perception information corresponding to the traffic sign line in response to the detection that the traffic sign line meets the preset passage assistance conditions. The scene perception information includes the operating status information of adjacent vehicles and lane attribute information. The risk level assessment module is used to assess the risk level of the road scene corresponding to the traffic sign based on the scene perception information, and obtain the risk assessment result. The access control module is used to execute the corresponding access control strategy based on the risk assessment results.
[0014] In addition, to achieve the above objectives, this application also proposes a vehicle, which includes: a memory, a processor, and a traffic assistance program stored in the memory and executable on the processor, the traffic assistance program being configured to implement the steps of the traffic assistance method as described above.
[0015] In addition, to achieve the above objectives, this application also provides a storage medium storing a program for implementing a passage assistance method, the program for implementing the passage assistance method being executed by a processor to implement the steps of the passage assistance method as described above.
[0016] This application provides a traffic assistance method, apparatus, device, and storage medium. The method includes: in response to detecting that a traffic sign meets preset traffic assistance conditions, acquiring scene perception information corresponding to the traffic sign, the scene perception information including adjacent vehicle operating status information and lane attribute information; assessing the risk level of the road scene corresponding to the traffic sign based on the scene perception information, obtaining a risk assessment result; and executing a corresponding traffic control strategy based on the risk assessment result. This application can automatically perform autonomous risk assessment based on environmental perception information when the traffic sign meets the preset traffic assistance conditions, and make risk classification decisions based on the risk assessment results, thereby improving traffic safety. Attached Figure Description
[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This is a flowchart illustrating the first embodiment of the passage assistance method of this application; Figure 2 This is a flowchart illustrating the second embodiment of the passage assistance method of this application; Figure 3 This is a schematic diagram of a first high-risk scenario in the second embodiment of the passage assistance method of this application; Figure 4 This is a schematic diagram of a second high-risk scenario for the second embodiment of the passage assistance method of this application; Figure 5 This is a schematic diagram of a third high-risk scenario in the second embodiment of the passage assistance method of this application; Figure 6 This is a schematic diagram of the fourth high-risk scenario of the second embodiment of the passage assistance method of this application; Figure 7 This is a schematic diagram of a medium-risk scenario in the second embodiment of the passage assistance method of this application; Figure 8 This is a schematic diagram of a first low-risk scenario of the second embodiment of the passage assistance method of this application; Figure 9 This is a schematic diagram of a second low-risk scenario for the second embodiment of the passage assistance method of this application; Figure 10 This is a schematic diagram of the module structure of the passage assistance device according to an embodiment of this application; Figure 11 This is a schematic diagram of the device structure of the hardware operating environment involved in the passage assistance method in the embodiments of this application.
[0020] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation
[0021] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.
[0022] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.
[0023] The main solution of this application is as follows: in response to the detection that the traffic markings meet the preset traffic assistance conditions, the scene perception information corresponding to the traffic markings is obtained, including the operating status information of adjacent vehicles and lane attribute information; based on the scene perception information, the risk level of the road scene corresponding to the traffic markings is assessed to obtain the risk assessment result; and the corresponding traffic control strategy is executed according to the risk assessment result.
[0024] In existing technologies, LCCs can only decide whether to stop or proceed at a steady speed by recognizing the lateral movement of pedestrians within the zebra crossing's field of vision. When pedestrians are obscured by obstacles and are not perceived, it can easily lead to collision risks.
[0025] This application achieves intelligent traffic through scenario determination, risk classification, and differentiated control strategies. Specifically, when traffic signs meet preset traffic assistance conditions, this application can automatically conduct autonomous risk assessment based on environmental perception information and make risk classification decisions based on the risk assessment results, thereby improving traffic safety.
[0026] It should be noted that the executing entity in this embodiment can be a traffic assistance system, or a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, mobile phone, vehicle terminal, etc., or a vehicle capable of performing the above functions, such as a vehicle, etc. This embodiment does not specifically limit it. The following uses a vehicle terminal as the executing entity as an example to describe this embodiment and the following embodiments.
[0027] Based on this, the embodiments of this application provide a passage assistance method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the passage assistance method of this application.
[0028] In this embodiment, the passage assistance method includes steps S10 to S30: Step S10: In response to detecting that the traffic sign line meets the preset traffic assistance conditions, the scene perception information corresponding to the traffic sign line is obtained. The scene perception information includes the operating status information of adjacent vehicles and lane attribute information. It is understandable that traffic markings can be core road markings that require vehicles to implement special traffic strategies, such as zebra crossings and turning lines; in this embodiment, they may specifically refer to zebra crossings. The aforementioned preset traffic assistance conditions can be pre-judgment conditions that trigger the traffic assistance proposed in this embodiment, used to filter out zebra crossing scenarios requiring special control.
[0029] Therefore, the vehicle terminal can receive road sign information collected by ADAS perception modules (cameras, radar, etc.) in real time. When a zebra crossing is detected ahead, the system can first initiate a judgment process for preset traffic assistance conditions. In one feasible implementation, in this embodiment, steps A1 to A3 may be included before step S10: Step A1: Obtain the actual perceived length of the traffic sign lines; Step A2: Obtain the traffic signal status corresponding to the traffic sign line; Step A3: If the actual perceived length is less than the theoretical length of the traffic sign and the traffic signal status is that no traffic light is detected, it is determined that the traffic sign meets the preset passage assistance conditions.
[0030] It's easy to understand that the aforementioned actual perceived length can be the identifiable length of the zebra crossing from the image captured by the ADAS camera, calculated by the image recognition algorithm built into the vehicle terminal. In other words, the vehicle terminal can control the ADAS camera to capture images of the zebra crossing ahead in real time, and then obtain the actual perceived length of the zebra crossing through built-in image segmentation and length calculation algorithms. The aforementioned theoretical length of the crosswalk marking can be considered the theoretical length of the zebra crossing that a vehicle should be able to recognize. This theoretical length can be determined based on the standard zebra crossing length, which is the theoretical total length of the zebra crossing starting from the left guardrail / double yellow line and ending at the right curb. The vehicle-mounted terminal can obtain this length from an in-vehicle map or road survey data. Therefore, the formula for calculating the theoretical length of the crosswalk marking can be: L (theoretical length) = L (standard length) * (1 - number of lanes * 0.02), where the number of lanes can also be obtained from an in-vehicle map or road survey data.
[0031] Understandably, the aforementioned traffic signal status can be the traffic light status at the zebra crossing in front of the vehicle, which can be determined by the traffic light recognition module of the ADAS camera.
[0032] Therefore, when the vehicle terminal detects that the actual perceived length is ≤ L (standard length) * (1 - number of lanes * 0.02) (i.e. the zebra crossing is obstructed) and the traffic signal status is that no traffic light is detected, it can be determined that the preset passage assistance conditions are met, and subsequent scene perception and risk assessment steps need to be triggered.
[0033] This implementation method achieves accurate identification of obstructed scenes and non-light-controlled intersections through a dual judgment mechanism of length ratio calculation and signal status detection, thereby improving the accuracy of system response.
[0034] It is easy to understand that the above-mentioned scene perception information can be the surrounding road environment data collected by the vehicle's ADAS system for risk assessment. It can include the operating status information of neighboring vehicles, such as the position, speed, braking status, and turn signal status of neighboring vehicles, as well as lane attribute information, such as the lane's steering attributes, lane spacing, and the relative position of the lane and the roadside.
[0035] For example, if the vehicle terminal determines that the preset traffic assistance conditions are met, it can immediately instruct the ADAS perception module to synchronously collect the operating status information of neighboring vehicles and lane attribute information. Among them, the operating status information of neighboring vehicles can be obtained by millimeter-wave radar to obtain the vehicle speed and braking deceleration, and the turn signal status of neighboring vehicles can be identified by camera; the lane attribute information can be obtained by vehicle network map or lane sign recognition module.
[0036] Step S20: Based on the scene perception information, perform a risk level assessment on the road scene corresponding to the traffic sign line to obtain a risk assessment result; Step S30: Execute the corresponding access control strategy based on the risk assessment results.
[0037] Understandably, the onboard terminal can classify the collision risk of the current zebra crossing scenario based on scene perception information according to preset risk assessment rules, i.e., perform risk level assessment, and determine the current matching risk level from different pre-set risk level scenarios, i.e., the aforementioned risk assessment result. Correspondingly, the aforementioned traffic control strategy can be a set of differentiated braking, warning, and exit operations pre-executed by the vehicle's LCC system for different risk level scenarios. At this time, the onboard terminal can invoke the corresponding control logic based on the risk assessment result, driving the vehicle's braking system and human-machine interface module to perform differentiated operations until the exit conditions are met.
[0038] This embodiment addresses the issue that existing LCC functions lack mechanisms for determining occlusion and classifying risks in crosswalks without traffic lights, relying solely on pedestrian perception for decision-making, which can easily lead to safety hazards due to obstructed views. This embodiment achieves accurate identification of complex crosswalk scenarios through pre-emptive screening of traffic assistance conditions and comprehensive scene perception, laying the foundation for subsequent risk classification and differentiated management, thus improving the safety of LCC functions in special crosswalk scenarios from the source.
[0039] This embodiment provides a traffic assistance method, which includes: obtaining the actual perceived length of a traffic sign line; obtaining the traffic signal status corresponding to the traffic sign line; and determining that the traffic sign line meets preset traffic assistance conditions when the actual perceived length is less than the theoretical length of the sign line and the traffic signal status is "no traffic light detected". In response to detecting that the traffic sign line meets the preset traffic assistance conditions, scene perception information corresponding to the traffic sign line is obtained, including adjacent vehicle operating status information and lane attribute information; a risk level assessment is performed on the road scene corresponding to the traffic sign line based on the scene perception information to obtain a risk assessment result; and a corresponding traffic control strategy is executed according to the risk assessment result. This embodiment achieves accurate identification of complex zebra crossing scenarios through pre-selection of traffic assistance conditions and full-dimensional scene perception, laying the foundation for subsequent risk classification and differentiated management, and improving the traffic safety of LCC function in special zebra crossing scenarios from the source. Simultaneously, this embodiment clarifies the trigger boundary of the traffic assistance function through a composite determination of zebra crossing occlusion status and no traffic light status, ensuring that the strategy is only activated in the target scenario, thus improving the adaptability accuracy of the method.
[0040] Based on the first embodiment of this application, in the second embodiment of this application, the same or similar content as the first embodiment described above can be referred to the above description, and will not be repeated hereafter.
[0041] Based on the first embodiment, in this embodiment, the vehicle terminal can classify the risk level of the current zebra crossing scenario according to the preset risk assessment rules, and obtain the assessment results of high / medium / low risk.
[0042] In the first feasible implementation, please refer to Figure 2 , Figure 2 This is a flowchart illustrating the second embodiment of the passage assistance method of this application. In this embodiment, step S20 may include steps B1 to B3: Step B1: When a preset braking state is detected in the neighbor vehicle operating status information, the number of braking neighbor vehicles corresponding to the vehicle in the braking state is obtained. Step B2: Obtain the braking lane position corresponding to the vehicle in the braking state based on the lane attribute information. Step B3: When the number of adjacent vehicles braking and the direction of the braking lane meet the preset high-risk conditions, the scenario is determined to be high-risk.
[0043] It should be noted that the aforementioned preset braking state can be the braking deceleration of a neighboring vehicle reaching or exceeding the deceleration required to bring it to a complete stop within a preset distance (S_stop) from the zebra crossing stop line, or the state where the neighboring vehicle has already come to a complete stop within the S_stop range. The value range of S_stop can be calibrated according to the vehicle model. At this time, the on-board terminal can periodically detect the motion information (distance, speed, acceleration, angle, orientation, etc.) of neighboring vehicles through image data collected by the monocular camera in the ADAS perception module, radar data collected by the millimeter-wave radar, the vehicle speed calculated by the wheel speed sensor, and the pose information calculated by the inertial navigation element. By comparing the detected information from previous and subsequent frames, it can identify whether the neighboring vehicles are in a state of acceleration or deceleration (relative distance increasing or decreasing) or are in a state of stillness (speed continuously 0 or below a predetermined minimum threshold), thereby achieving real-time fitting of the operating state of the vehicle's neighboring vehicles. Finally, when any neighboring vehicle is detected braking, its braking deceleration is calculated, and neighboring vehicles in the aforementioned preset braking state are selected.
[0044] Understandably, the aforementioned number of adjacent vehicles braking can be the number of adjacent vehicles in a preset braking state, which is a core quantitative indicator for determining high-risk scenarios. The aforementioned braking lane position can be the position of the lane where the adjacent vehicle in the preset braking state is located relative to the vehicle itself, i.e., the adjacent vehicle is located to the left of the vehicle, the adjacent vehicle is located to the right of the vehicle, the adjacent vehicle is located in the adjacent lane, or the adjacent vehicle is located in the next lane, etc. In this case, the on-board terminal can combine lane attribute information to determine the lateral distance (number of lanes) between the lane where the braking adjacent vehicle is located and the vehicle itself, such as "braking adjacent vehicle in 1 lane to the left of the vehicle", "braking adjacent vehicle in 2 lanes to the right of the vehicle", etc.
[0045] The aforementioned preset high-risk conditions can be composite logical conditions for determining high-risk scenarios, determined jointly by the number of adjacent vehicles braking and the direction of the braking lane. In this embodiment, the preset high-risk conditions may include: at least one lane to the left of the vehicle and at least one lane to the right of the vehicle having adjacent vehicles in a preset braking state; at least two lanes to the left or right of the vehicle having adjacent vehicles in a preset braking state; adjacent vehicles in a preset braking state on a straight lane other than the vehicle's own lane; and adjacent vehicles separated by only one lane to the left or right of the vehicle having preset braking states.
[0046] For ease of understanding, please refer to Figures 3-6 Provide an explanation. Figure 3 This is a schematic diagram of a first high-risk scenario in the second embodiment of the passage assistance method of this application. Figure 4 This is a schematic diagram of a second high-risk scenario for the second embodiment of the passage assistance method of this application. Figure 5This is a schematic diagram of a third high-risk scenario in the second embodiment of the passage assistance method of this application. Figure 6 This is a schematic diagram of a fourth high-risk scenario for the second embodiment of the passage assistance method of this application. For example... Figure 3 As shown, when the vehicle terminal detects that there are ≥1 vehicles in the left lane and ≥1 vehicles in the right lane in front of the vehicle based on the number of adjacent vehicles and the direction of the braking lane, and meets the preset braking state, that is, when the vehicle stops at a distance Sstop = (-3m, 1m) from the zebra crossing stop line (the range can be marked, negative values indicate that the vehicle has not reached the stop line, and positive values indicate that the vehicle has crossed the stop line), or when the vehicle is braking at a deceleration greater than or equal to that within the Sstop range, it can be determined as a high-risk scenario.
[0047] like Figure 4 As shown, when the vehicle terminal detects, based on the number of adjacent vehicles braking and the direction of the braking lane, that there are ≥2 vehicles on the left side of the vehicle and ≥2 vehicles on the right side of the vehicle braking to a stop at a distance of Sstop = (-3m, 1m) from the zebra crossing stop line, or is braking at a deceleration greater than or equal to that within the Sstop range, it can be determined as a high-risk scenario.
[0048] like Figure 5 As shown, when the vehicle terminal detects a vehicle in the straight lane ahead of the vehicle (in this case, there is no limit to the lateral distance between the vehicle and the vehicle, and the vehicle may be crossing two or more lanes with the vehicle in front) based on the number of adjacent vehicles and the direction of the braking lane, and the vehicle stops at a distance of Sstop = (-3m, 1m) from the stop line or is braking at a deceleration greater than or equal to that within the Sstop range, it can be identified as a high-risk scenario.
[0049] like Figure 6 As shown, when the vehicle terminal detects based on the number of adjacent vehicles braking and the braking lane orientation that the current lane is a two-lane lane, and the distance between the vehicle on the left or right in front and the vehicle in the lane is 1, and the vehicle is braking at a distance of Sstop = (-3m, 1m) from the stop line or is braking at a deceleration sufficient to stop within the Sstop range; In summary, when the vehicle terminal activates LCC during driving, if the ADAS perception module detects that there are vehicles stopping within a certain range of the zebra crossing on both the left and right sides in front of the vehicle, or vehicles from two or more lanes on either side stopping within a certain range of the zebra crossing, or only one vehicle in the straight lane or an adjacent lane stopping in front of the zebra crossing, then the vehicle is considered to have met the above conditions. Figures 3-6 If any scenario's judgment logic is triggered, it can be identified as a high-risk scenario. Therefore, this embodiment can establish clear high-risk scenario judgment rules by quantifying the number and location of adjacent vehicles braking, thereby accurately identifying high-collision-risk scenarios and providing precise triggering basis for subsequent emergency braking strategies.
[0050] It is easy to understand that when a high-risk scenario is detected, the vehicle terminal can execute a corresponding high-risk passage strategy. As one possible implementation, in this embodiment, step S30 includes steps S31 to S33: Step S31: When the risk assessment result is the high-risk scenario, obtain the early warning information corresponding to the high-risk scenario; Step S32: Determine the target braking deceleration based on the target braking distance and the current vehicle speed; Step S33: Execute a preset braking strategy based on the warning information, the target braking deceleration, and the target braking distance until the preset passage assistance conditions are not met, at which point the preset braking strategy is exited.
[0051] It is understandable that the aforementioned warning messages can be sent from the vehicle terminal to the vehicle's human-machine interface module (instrument panel, HUD, vehicle infotainment system, etc.) to remind the driver with audio-visual or textual information, such as a voice prompt saying "Please be aware of pedestrians" or activating the instrument panel warning lights. Therefore, when a high-risk scenario is determined, the vehicle terminal can retrieve the built-in high-risk warning messages, send instructions to the vehicle's human-machine interface module, and trigger a warning with a continuously calibrated duration to avoid confusing the driver due to sudden braking.
[0052] The aforementioned target braking deceleration can be a preset vehicle braking deceleration threshold to ensure both driving comfort and braking safety. In high-risk scenarios, it must meet both comfort and effective stopping requirements. Similarly, the aforementioned target braking distance can be a preset safe distance at which the vehicle can stop before the stop line at a zebra crossing, determined by data collected by a camera. At this point, the onboard terminal can calculate the target braking deceleration *a* based on the current vehicle speed (Vt) using the formula *a = -Vt² / 2Xt*. Here, *Xt* is the target braking distance, and the deceleration must meet the comfort threshold of *a* ≥ -2.5 m / s². Of course, if the remaining target braking distance is insufficient to maintain this deceleration requirement, the deceleration can be automatically increased to prioritize stopping before the stop line.
[0053] At this point, the complete braking control logic in high-risk scenarios, namely the aforementioned preset braking strategy, can include three sub-steps: warning, braking execution, and strategy exit. That is, the onboard terminal can send braking commands to the vehicle's brake actuators to achieve automatic braking that balances comfort and safety based on the calculated target deceleration and the actual target braking distance.
[0054] In addition, the onboard terminal monitors scene changes in real time. When it detects that a vehicle (its own vehicle or a neighboring vehicle) has passed the zebra crossing, or the zebra crossing obstruction is removed (i.e., the vehicle has a complete view of the zebra crossing and there are no pedestrians), or when it detects traffic lights, it can respond to the above-mentioned "failure to meet the preset passage assistance conditions" and exit the preset braking strategy. If a pedestrian is crossing after exiting the preset braking strategy, the LCC will wait for the pedestrian to cross, and after the pedestrian has crossed, it will continue to cruise at the set speed according to the current activation cycle.
[0055] Therefore, this embodiment can balance safety and driving comfort in high-risk scenarios through comfortable deceleration braking and forward human-machine warning, while clear exit conditions ensure traffic efficiency and avoid vehicles being stuck at intersections for a long time.
[0056] In a second feasible implementation, step S20 may include steps C1-C2: Step C1: When a turning state is detected in the neighboring vehicle's operating status information, the turning lane information and turning lane spacing corresponding to the vehicle in the turning state are obtained according to the lane attribute information. Step C2: If the turning lane information matches the preset turning lane, the turning lane spacing is greater than the preset vehicle spacing, and the vehicle in the turning state brakes, it is determined to be a medium-risk scenario.
[0057] It is easy to understand that the above-mentioned turning state can represent the operating state of a neighboring vehicle with its left / right turn signal on and its body posture or driving trajectory showing a turning trend. At this time, the vehicle terminal can identify the turn signal status of the neighboring vehicle through the ADAS camera, and at the same time, combine the trajectory data of the neighboring vehicle collected by the radar to determine whether the neighboring vehicle is in a turning state.
[0058] The aforementioned turning lane information can be the attribute of the lane where the adjacent vehicle is located. The preset turning lanes can include different lanes such as left-turn lanes, right-turn lanes, straight-ahead + left-turn lanes, or straight-ahead + right-turn lanes. The vehicle terminal can obtain this information through an onboard network map or lane sign recognition module. The aforementioned turning lane spacing can be the number of lateral lanes between the vehicle and an adjacent vehicle in a turning state, and is a key spacing indicator for determining risk scenarios in this embodiment. At this time, the vehicle terminal can retrieve lane attribute information, confirm the turning attribute of the lane where the adjacent vehicle is located, and simultaneously count the number of lateral lanes between the vehicle and the adjacent vehicle to obtain the turning lane spacing.
[0059] At this point, the preset vehicle spacing can be a pre-set threshold for the number of lanes distinguishing between medium and high risk. In this embodiment, the specific value can be 2 lanes. That is, in this embodiment, when the vehicle terminal detects that a neighboring vehicle is turning, the lane it is in is a turning-related lane, the lane spacing between turning lanes is ≥2 lanes, and the neighboring vehicle is in a preset braking state (i.e., braking at a deceleration greater than or equal to that required to stop within the Sstop range), it can determine that a medium-risk scenario has occurred. For ease of understanding, refer to... Figure 7 To illustrate, Figure 7 This is a schematic diagram of a medium-risk scenario for the second embodiment of the passage assistance method of this application. For example... Figure 7 As shown, in this scenario, a vehicle in the left-turn lane that brakes sharply may only be preparing to turn left, make a U-turn, or turn right, rather than avoiding a pedestrian. However, it is impossible to assess whether the vehicle is preparing to turn while also avoiding a pedestrian. In other words, there is still a risk of a pedestrian crossing the road. Therefore, braking and alerting the driver are still necessary to reduce the risk.
[0060] At this point, due to the greater lateral distance between the vehicle and adjacent vehicles, and better visibility, if a pedestrian is detected crossing the zebra crossing as the vehicle approaches, there is more time to brake and avoid them. Therefore, a deceleration rather than a complete stop control strategy can be implemented. The vehicle can reduce its speed more comfortably by slowing down, without having to brake directly to a stop, thus reducing excessive vehicle start-stop processes to avoid affecting traffic efficiency and driving experience.
[0061] At this point, the onboard terminal can calculate the target braking deceleration (which must be greater than or equal to the medium-risk comfort deceleration, for example, -1.5 m / s²) and reduce the vehicle speed to a preset safe speed (30 km / h). If the current vehicle speed is already below 30 km / h, braking will not be performed. Simultaneously, a human-machine warning consistent with that in high-risk scenarios is triggered. Similarly, when the preset traffic assistance conditions are not met, the control strategy in the medium-risk scenario can be automatically exited. Therefore, this implementation method achieves accurate identification of medium-risk scenarios through the joint determination of steering status and lane attributes, and adopts a strategy of deceleration without braking, thus balancing traffic safety and intersection traffic efficiency.
[0062] As one possible implementation, in this embodiment, step C1 may be followed by: Step C3: If the turning lane information matches the preset straight lane, the turning lane spacing is less than the preset vehicle spacing, and the vehicle in the turning state brakes, it is determined to be a low-risk scenario.
[0063] Understandably, the aforementioned preset straight lane can be a lane that only allows straight travel and has a curb alongside it; it has no turning attribute and is determined directly by the lane attribute information. It's easy to understand that, assuming the adjacent vehicle is close to the driver, the driver has good visibility, and sufficient emergency braking response time, if the adjacent vehicle is in a straight lane near the curb and is turning or braking, the adjacent vehicle is likely stopping temporarily rather than yielding to a pedestrian. This can be considered a low-risk scenario. For easier understanding, please refer to... Figure 8 , Figure 8 This is a schematic diagram of a first low-risk scenario for the second embodiment of the passage assistance method of this application. For example... Figure 8 As shown, if the distance between the vehicle on the right and the vehicle in front is less than or equal to the preset lane spacing of 2, and the vehicle is braking at a deceleration greater than or equal to that required to stop within the Sstop range, and if the vehicle changes lanes to the right and the right side of the target lane is a curb, the braking of the adjacent vehicle is likely an abnormal operation. Since the vehicle has good visibility, there is no need for active braking.
[0064] Understandably, in low-risk scenarios, the vehicle terminal can perform brake pre-filling, that is, send a command to the braking system requesting brake pre-filling. Brake pre-filling can pre-pressurize the brake fluid without the driver noticing, reducing the gap between the brake disc and brake pads. This ensures that if braking is needed later, braking can be performed more quickly, thereby reducing braking distance and improving safety. At the same time, there are corresponding human-machine interaction warning strategies and exit logic in this scenario, consistent with the logic of the high-risk and medium-risk scenarios mentioned above, which will not be elaborated here.
[0065] In a third feasible implementation, step S20 may include steps D1-D2: Step D1: When a stopped state is detected in the neighboring vehicle running status information, the stopping lane information and stopping lane spacing corresponding to the vehicle in the stopped state are obtained according to the lane attribute information. Step D2: If the stopping lane information matches the preset boundary lane and the stopping lane spacing is greater than the preset vehicle spacing, the scenario is determined to be low-risk.
[0066] It is easy to understand that the aforementioned stopped state can be an operating state in which the speed of the adjacent vehicle is 0 and the duration is greater than or equal to a preset duration (5s in this embodiment), which can be determined based on the continuous monitoring results of the ADAS radar. For example, when the vehicle terminal reflects that the speed of the adjacent vehicle is 0 and the duration is greater than or equal to 5s through the real-time monitoring information of the adjacent vehicle by the ADAS radar, it can be determined as a stopped state.
[0067] The aforementioned stop lane information can be the location attribute of the lane where a neighboring vehicle is stopped. In this case, the aforementioned preset boundary lane can represent a lane where either side is the road edge. It is understandable that the aforementioned stop lane spacing can be the number of lateral lanes between the vehicle and its neighboring vehicle that is stopped. As mentioned above, the preset vehicle spacing can be 2 lanes.
[0068] It should be noted that, referring to Figure 9 To illustrate, Figure 9 This is a schematic diagram of a second low-risk scenario for the second embodiment of the passage assistance method of this application. For example... Figure 9 As shown, if the vehicle terminal detects a vehicle on its right in front of it that is at least two lanes away from it, and the right side of that lane is a curb, and the vehicle's speed is 0 for at least 5 seconds (calibrable) after the target is detected by the perception module, then a low-risk scenario can be identified. Similarly, the vehicle terminal can send a brake pre-fill command to the braking system to pre-pressurize the brake fluid and reduce the gap between the brake disc and brake pads; at the same time, it can trigger a human-machine warning, and the strategy will be discontinued after the vehicle crosses the zebra crossing.
[0069] Therefore, this implementation method can distinguish between parked vehicles and vehicles yielding to pedestrians by determining the boundary attributes and spacing of the stopping lane, and uses pre-filling braking instead of active braking in this process, thereby improving emergency safety without affecting traffic efficiency.
[0070] The above are only three feasible implementation methods of step S20 provided in this embodiment. This embodiment does not specifically limit the specific implementation method of step S20.
[0071] In summary, this embodiment can optimize the strategy of using LCC to cross the road in zebra crossings without traffic lights, clarify the judgment conditions for different risk scenarios, and make flexible responses according to the risk level of different scenarios, thereby improving safety and user experience.
[0072] This embodiment discloses that when a preset braking state is detected in the neighboring vehicle operating status information, the number of braking neighboring vehicles corresponding to the vehicle in the braking state is obtained; the braking lane orientation corresponding to the vehicle in the braking state is obtained according to the lane attribute information; when the number of braking neighboring vehicles and the braking lane orientation meet preset high-risk conditions, it is determined to be a high-risk scenario. When the risk assessment result is the high-risk scenario, the warning prompt information corresponding to the high-risk scenario is obtained; the target braking deceleration is determined according to the target braking distance and the current vehicle speed; a preset braking strategy is executed based on the warning prompt information, the target braking deceleration, and the target braking distance, until the preset traffic assistance conditions are detected and the preset braking strategy is exited.
[0073] When a turning state is detected in the adjacent vehicle's operating status information, the turning lane information and turning lane spacing corresponding to the vehicle in the turning state are obtained based on the lane attribute information. If the turning lane information matches a preset turning lane, the turning lane spacing is greater than a preset vehicle spacing, and the vehicle in the turning state brakes, it is determined to be a medium-risk scenario. If the turning lane information matches a preset straight lane, the turning lane spacing is less than a preset vehicle spacing, and the vehicle in the turning state brakes, it is determined to be a low-risk scenario.
[0074] When a stopped state is detected in the neighboring vehicle's operating status information, the stopping lane information and stopping lane spacing corresponding to the stopped vehicle are obtained according to the lane attribute information; if the stopping lane information conforms to the preset boundary lane and the stopping lane spacing is greater than the preset vehicle spacing, it is determined to be a low-risk scenario.
[0075] This embodiment can optimize the strategy of using LCC to cross the road in zebra crossings without traffic lights, clarify the judgment conditions for different risk scenarios, and make flexible responses according to the risk level of different scenarios, thereby improving safety and user experience.
[0076] This application also provides a passage assistance device, please refer to... Figure 10 , Figure 10 This is a schematic diagram of the module structure of the passage assistance device according to an embodiment of this application. In this embodiment, the passage assistance device includes: The auxiliary start module T1 is used to obtain scene perception information corresponding to the traffic sign line in response to detecting that the traffic sign line meets the preset passage assistance conditions. The scene perception information includes the operating status information of adjacent vehicles and lane attribute information. The risk level assessment module T2 is used to assess the risk level of the road scene corresponding to the traffic sign based on the scene perception information, and obtain the risk assessment result. The access control module T3 is used to execute the corresponding access control strategy based on the risk assessment results.
[0077] Optionally, in this embodiment, the risk level assessment module T2 is further configured to, when a preset braking state is detected in the neighboring vehicle operating status information, obtain the number of braking neighboring vehicles corresponding to the vehicle in the braking state; obtain the braking lane orientation corresponding to the vehicle in the braking state according to the lane attribute information; and determine it as a high-risk scenario when the number of braking neighboring vehicles and the braking lane orientation meet the preset high-risk conditions.
[0078] Optionally, in this embodiment, the passage control module T3 is further configured to: acquire warning information corresponding to the high-risk scenario when the risk assessment result is the high-risk scenario; determine the target braking deceleration based on the target braking distance and the current vehicle speed; execute a preset braking strategy based on the warning information, the target braking deceleration and the target braking distance, until the preset passage assistance conditions are not met and the preset braking strategy is exited.
[0079] Optionally, in this embodiment, the risk level assessment module T2 is further configured to, when a turning state is detected in the neighboring vehicle's operating status information, obtain the turning lane information and turning lane spacing corresponding to the vehicle in the turning state according to the lane attribute information; and determine it as a medium-risk scenario when the turning lane information matches a preset turning lane, the turning lane spacing is greater than a preset vehicle spacing, and the vehicle in the turning state brakes.
[0080] Optionally, in this embodiment, the risk level assessment module T2 is further used to determine a low-risk scenario when the turning lane information matches the preset straight lane, the turning lane spacing is less than the preset vehicle spacing, and the vehicle in the turning state brakes.
[0081] Optionally, in this embodiment, the risk level assessment module T2 is further configured to, when a stopped state is detected in the neighboring vehicle's operating status information, obtain the stopping lane information and stopping lane spacing corresponding to the vehicle in the stopped state based on the lane attribute information; and determine the scenario as low-risk if the stopping lane information conforms to a preset boundary lane and the stopping lane spacing is greater than a preset vehicle spacing.
[0082] Optionally, in this embodiment, the auxiliary start module T1 is further configured to obtain the actual perceived length of the traffic sign line; obtain the traffic signal status corresponding to the traffic sign line; and determine that the traffic sign line meets the preset passage assistance conditions when the actual perceived length is less than the theoretical sign line length and the traffic signal status is that no traffic light is detected.
[0083] The passage assistance device provided in this application, employing the passage assistance method in the above embodiments, can solve the technical problem of passage assistance. Compared with the prior art, the beneficial effects of the passage assistance device provided in this application are the same as those of the passage assistance method provided in the above embodiments, and other technical features in the passage assistance device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.
[0084] This application provides a vehicle, the vehicle including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the traffic assistance method in Embodiment 1 above.
[0085] The following is for reference. Figure 11 It shows a structural schematic diagram of a vehicle suitable for implementing the embodiments of this application. Figure 11 The vehicle shown is merely an example and should not be construed as limiting the functionality or scope of the embodiments described in this application. Figure 11 As shown, the vehicle may include a processing unit 1001 (e.g., a central processing unit, a graphics processor, etc.) that can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for vehicle operation. The processing unit 1001, the ROM 1002, and the RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows communication aids to communicate wirelessly or wiredly with other devices to exchange data. Although vehicles with various systems are shown in the figures, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.
[0086] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a access assistance program product comprising an access assistance program carried on a computer-readable medium, the access assistance program containing program code for performing the methods shown in the flowcharts. In such embodiments, the access assistance program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from read-only memory 1002. When the access assistance program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.
[0087] The vehicle provided in this application, employing the traffic assistance method described in the above embodiments, can solve the technical problem of how to achieve proactive response to complex intersection environments and improve traffic safety. Compared with the prior art, the beneficial effects of the vehicle provided in this application are the same as those of the traffic assistance method provided in the above embodiments, and other technical features of the vehicle are the same as those disclosed in the previous embodiment method, and will not be repeated here.
[0088] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.
[0089] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
[0090] This application provides a storage medium having computer-readable program instructions (i.e., access assistance program) stored thereon, which are used to execute the access assistance method in the above embodiments.
[0091] The storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of the storage medium may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.
[0092] The aforementioned storage medium may be included in the vehicle or may exist independently without being installed in the vehicle.
[0093] The aforementioned storage medium carries one or more programs, which, when executed by the vehicle, enable the vehicle to: provide passage assistance.
[0094] Commonly used auxiliary program code for performing the operations of this application can be written in one or more programming languages or a combination thereof. These programming languages include object-oriented programming languages—such as Java, Smalltalk, and C++—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0095] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and access assistance products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.
[0096] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.
[0097] The readable storage medium provided in this application is a storage medium that stores computer-readable program instructions (i.e., a traffic assistance program) for executing the above-described traffic assistance method. This solves the technical problem of how to achieve proactive response to complex intersection environments and improve traffic safety. Compared with the prior art, the beneficial effects of the storage medium provided in this application are the same as those of the traffic assistance method provided in the above embodiments, and will not be repeated here.
[0098] The above are only some embodiments of this application and do not limit the scope of the solution of this application. All equivalent structural transformations made under the technical concept of this application and using the content of this application specification and drawings, or direct / indirect applications in other related technical fields, are included within the protection scope of this application.
Claims
1. A method for assisting passage, characterized in that, The method includes: In response to detecting that the traffic sign line meets the preset traffic assistance conditions, the scene perception information corresponding to the traffic sign line is obtained. The scene perception information includes the operating status information of adjacent vehicles and lane attribute information. Based on the scene perception information, a risk level assessment is performed on the road scene corresponding to the traffic sign line to obtain the risk assessment result. The corresponding access control strategy will be implemented based on the risk assessment results.
2. The passage assistance method as described in claim 1, characterized in that, The step of assessing the risk level of the road scene corresponding to the traffic signs based on the scene perception information and obtaining the risk assessment result includes: When a preset braking state is detected in the neighboring vehicle operating status information, the number of braking neighboring vehicles corresponding to the vehicle in the braking state is obtained. The braking lane position corresponding to the vehicle in the braking state is obtained based on the lane attribute information. When the number of adjacent vehicles braking and the direction of the braking lane meet the preset high-risk conditions, the scenario is determined to be high-risk.
3. The passage assistance method as described in claim 2, characterized in that, The step of implementing the corresponding access control strategy based on the risk assessment results includes: When the risk assessment result is a high-risk scenario, obtain the early warning information corresponding to the high-risk scenario; Determine the target braking deceleration based on the target braking distance and the current vehicle speed; Based on the warning information, the target braking deceleration, and the target braking distance, a preset braking strategy is executed until the preset passage assistance conditions are not met, at which point the preset braking strategy is exited.
4. The passage assistance method as described in claim 1, characterized in that, The step of assessing the risk level of the road scene corresponding to the traffic signs based on the scene perception information and obtaining the risk assessment result includes: When a turning state is detected in the neighboring vehicle's operating status information, the turning lane information and turning lane spacing corresponding to the vehicle in the turning state are obtained according to the lane attribute information. If the turning lane information matches the preset turning lane, the turning lane spacing is greater than the preset vehicle spacing, and the vehicle in the turning state brakes, it is determined to be a medium-risk scenario.
5. The passage assistance method as described in claim 4, characterized in that, When a turning state is detected in the neighboring vehicle's operating status information, after obtaining the turning lane information and turning lane spacing corresponding to the vehicle in the turning state based on the lane attribute information, the method further includes: If the turning lane information matches the preset straight lane, the turning lane spacing is less than the preset vehicle spacing, and the vehicle in the turning state brakes, it is determined to be a low-risk scenario.
6. The passage assistance method as described in claim 1, characterized in that, The step of assessing the risk level of the road scene corresponding to the traffic signs based on the scene perception information and obtaining the risk assessment result includes: When a stopped state is detected in the neighboring vehicle's operating status information, the stopping lane information and stopping lane spacing corresponding to the vehicle in the stopped state are obtained according to the lane attribute information. If the stopping lane information matches the preset boundary lane and the stopping lane spacing is greater than the preset vehicle spacing, the scenario is determined to be low-risk.
7. The passage assistance method as described in claim 1, characterized in that, Before obtaining the scene perception information corresponding to the traffic sign line in response to detecting that the traffic sign line meets the preset traffic assistance conditions, the method further includes: Obtain the actual perceived length of traffic sign lines; Obtain the traffic signal status corresponding to the traffic sign line; If the actual perceived length is less than the theoretical length of the traffic marking line, and the traffic signal status is that no traffic light is detected, then the traffic marking line is determined to meet the preset passage assistance conditions.
8. A passage assistance device, characterized in that, The passage assistance device includes: The auxiliary start module is used to obtain scene perception information corresponding to the traffic sign line in response to the detection that the traffic sign line meets the preset passage assistance conditions. The scene perception information includes the operating status information of adjacent vehicles and lane attribute information. The risk level assessment module is used to assess the risk level of the road scene corresponding to the traffic sign based on the scene perception information, and obtain the risk assessment result. The access control module is used to execute the corresponding access control strategy based on the risk assessment results.
9. A vehicle, characterized in that, The vehicle includes: a memory, a processor, and a passage assistance program stored in the memory and executable on the processor, the passage assistance program being configured to implement the steps of the passage assistance method as described in any one of claims 1 to 7.
10. A storage medium, characterized in that, The storage medium stores a passage assistance program, which, when executed by a processor, implements the steps of the passage assistance method as described in any one of claims 1 to 7.